Graphic depiction of a bivariate distribution.

The value or category in a distribution with the highest frequency.

Indicates how much the dependent variable changes for every one-unit increase in the independent variable.

Consists of editing, coding, data entry, and data cleaning.

The middle value in a distribution.

Examples are Cramer’s phi and the correlation coefficient.

A cleaning technique that can be programmed for automatic detection in computer-assisted interviewing.

A graphic display of a univariate distribution.

Shows whether the association in a contingency table is statistically significant.

Replacing missing values in data analysis by estimating values from the available data.

Detecting and resolving errors in coding and data entry.

The numerical difference between an observed value and the value predicted by the regression line.

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